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Eliminating waste in OMS Projects

Eliminating waste in any kind of project is a good thing. OMS projects have specific ways they are most
prone to incurring waste. Wasting effort
affects an OMS project in 2 main ways.
Either it can use up limited amount of time on a calendar or it can add
cost through extra hours charged by team members. In cases where the deadlines are tight,
spending time on wasted tasks is especially undesirable for the project. The remaining tasks wind up getting squeezed
even tighter and can cause hurried actions that impact quality. Targeted planning designed specifically to
avoid waste is often not included in project plans, but should be. Project managers do important planning, such
as risk response planning, creating the WBS, scope management, and establishing
a communication plan. However, there is
often not enough attention specific to preventing waste in the project. In my 15 years of outage management
experience, I have found many places where waste has happened. This blog posting will describe some
scenarios I have seen in the past and are things to watch out for when planning
an OMS project. In coming up with the
list, I considered the memory aid "TIM WOOD", which stands for Transportation,
Inventory, Motion, Waiting, Over production, Over processing, and Defects.

Transportation

Transportation is a
large waste source. It is necessary to
ask yourself these questions: How critical is having an onsite presence is to
the project? When is it critical to have
the project team onsite? There are times
where an onsite presence is important and the team must be there, like
workshops and go live support. However,
there are other times where remote working is possible, like when the system is
being configured based on the defined requirements from the workshops. When the team is remote, not only is there
avoidance of travel costs, but also the time is not lost by traveling 2 days
each week. Those factors then are multiplied
by the number of team members traveling.
We live in an age where tools such as VPN, virtual machines, and web
conferencing enable more offsite work. I
have worked on multiple projects where much of the configuration and interface
development occurred off site. Once the
system is configured and the adapters built, they can be delivered to the
customer electronically. To make this
work, there must be good communication between the remote workers and the team
that is on site.

Inventory

Inventory in a software IT project isn't the same as
manufacturing a hard item, like a hard drive.
We aren't talking about ordering and stocking component parts. However there needs to be the appropriate
inventory of environments to support the project. Too many environments increase the effort
needed to maintain them. Not having enough
environments lead to either a team member waiting (another waste point) to use
the system or team members doing work that interferes with the other. An example of interference is when multiple
people need to work in the same file or when one person needs to perform system
restarts while another team member is doing other work in the system. To be able to have people working in multiple
systems, there must be good version control to make sure nothing is overwritten
as well. Even if team members are
working on completely different areas, there can be problems without a proper
inventory of environments. For example,
during testing, that test environment must remain stable. Introducing configuration or model changes
will affect system stability and the results seen from a test. Using that environment for any multiple
purposes has risks from interaction to changing configurations, or perceived
defects.

WAITING

Waiting is always a risk of waste in projects. There are some factors that are universal to
projects, like waiting for proper resources or waiting for dependant
tasks. I'll be writing only to more
specific to outage management. Some
aspects of waiting have already been mentioned as it can combine in other areas
as it did with inventory (environments).
One of the biggest risks for waiting in an outage management project is
waiting for the data quality to reach the necessary standards and be
stable. Many tasks are dependent on
having correct data. A novice to outage management may feel
overconfident in the GIS data's quality because it 'looks good' in the
GIS. However, OMS data must not only
look good, but have proper connectivity so that the power flow is properly
represented. It also needs to have
necessary device attribute information and correct phasing. On the development side, it is necessary to
ensure the configurations that go into the building of the OMS model from the
GIS data build the model as desired.
Performing the necessary reviews with corrections to the data or model
build configurations takes time and multiple iterations. Therefore, the data reviews need to start
early so that when the project is ready to enter into later phases, like test planning;
the data is stable so that results remain consistent. All types of devices must successfully build
into the model, the connectivity must be good, customers must map to the
correct premise, and a user looking for information to appear must be able to
see the correct information. If this
isn't done, it is necessary to wait to do test script writing because writing
them based on changing data will lead to the tests to be wrong and perceived
defects seen. Perceived defects will
happen because the test script's expected results will say one thing, but the
viewed result, while being correct, will show something else. Waiting to create test scripts then delays
the start of testing, which can lead to delaying the go live. When new data is introduced, customers and
devices change, which can and does change predictions. Even if testing can occur, if the data isn't
production ready, go live still must wait.
Wait can also come from seasonal causes.
During a utility's storm season, the utility's team members will have
less availability to the project. It is
important to plan activities that are less dependent on the utility's staff
during the storm season and time the estimated completion of work to be in the
calm weather season. Additionally it
would be unadvisable to bring a new system or a system upgrade to production
during the storm season, so it would be necessary to wait until it is
over. Plan the start of the project so
that the predicted end is in the calm season.

Over Production

Over production can happen when there isn't full commitment
to a task. When a project has tasks/goals
that "would be nice", those tasks are first tasks to be neglected as available
time begins to run out. I have seen with
other projects where time has been spent on time consuming goals that are "not critical"
to the project. These tasks wind up
being abandoned because other priorities take precedence or time runs out to
complete them. When tasks are abandoned,
the time spent on them is now wasted as far as the project is concerned.

Another over production habit is to making configurations
decisions too early in the project. This
can lead to "reinventing the wheel" by making configuration changes that
provide little or no benefit or finding that the choices don't work as well as
was hoped. OMS manufacturers have used
best practices to create a base product configuration. Sometimes it is necessary to deviate from a
Commercial Off The Shelf (COTS) configuration.
What is leanest is to make only make changes when needed and once they
are made, not to change them. Getting a
better understanding of how the COTS configuration works and how well it works
may avoid the need to make changes or change the configuration multiple times. Additionally, configurations unique to a
customer require additional maintenance efforts. By over configuring (processing) the OMS, effort
and cost increases.

OVER PROCESS

In a conservative and risk averse industry, like utilities, over
processing is a big waste risk. While it
is important to be thorough, being excessive is wasteful. When writing test scripts, it is easy to
write multiple scripts that test the same functionality, or often a utility may
rerun tests with multiple people doing the testing. Some overlap is good, but a lot is
excessive. The important thing is to
find the balance and lead the team to recognize when it is excessive. There is much to test in an OMS and there
will be defects that cause retesting, so it is important to not use up the time
retesting the same functionality too many times. In testing the OMS, regression testing is
important. Retesting after a patch
verifies not only the fix, but that the fix didn't break something else. Testing more than solely the fix is
needed. It is equally important to
target the additional tests for regression purposes to areas that the fix could
affect. If the fix is localized, it is
not necessary to retest the entire system.
It helps to understand what is in the fix when planning the regression
test so that the right amount is done

When planning fixes to apply to an OMS system, it is most
efficient to use the manufacturer's planned releases instead of pursuing
multiple one off fixes. There are
multiple time wastes in the one off fixes.
Each one off fix would be received separately. They would need separate testing, promotion
plans, and system downtime for the installation. Then at a later time the same fixes that were
the one off fixes are released as a part of a release point. By picking up that release point all the
fixes are available all at once. The
effort to test and implement is condensed into one effort and retesting the
same modules is not needed.

Data can be over processed as well. There are many details and objects that can
be built into the data model. However,
building every attribute of every device is wasteful. Some objects, like geographic objects, don't
need details built into the model. Other
devices may have attributes that aren't going to be important to outage
management. Building attributes takes up
space in the database and increases the time needed to build. Eliminating unnecessary processing saves
effort, build time, and disk space.

DEFECTS

Like any software product, defects are an unavoidable part
of the process. In fact if none are
found, questions as the thoroughness of testing would be raised. Since every defect that is written takes time
to process, it is important to limit the defects to 'real' defects. Try to avoid the creation of duplicate
defects. Even a duplicate carries a time
overhead to close out. In addition to
defects, another type of 'nonreal' defects is a Works As Designed defect. This is often the cause of a lack of understanding
of how the OMS works. These take even
more time away with more documentation and explanation necessary. With good communication, good training, and
using testers that understand the OMS, many of these can be avoided. This way effort is spend where it needs to
be, fixing actual problems with the software.
Issues that are perceived to be software defects can have an origin from
bad or changing data models. If the
model is updated without updating test scripts, testers may see counts or
predictions different than what is in the script. Because customers or devices may have been
added, removed, or moved, the result may be correct despite what the script
says. It is important to keep the data
model stable entering into testing until exiting. Investing time early in the data review
process is part of the solution to defects from bad data. If the data coming into the OMS is bad, it
will display bad information in dashboards or look strange in the map
viewer. If sufficient lead time is given
to ensuring data quality, many data origin defects can and will be
avoided. When resolving defects,
planning the process also minimizes the risk of additional defects and enables
a speedy closure of existing defects. It
is important not only that the defects get fixed by development, but also there
is a plan that says when, how, and by whom the fixes get promoted and
retested. I have seen many times where
an improperly deployed set of fixes leads to the belief that a fix did not
work, which leads to wasted time testing and having to perform another
deployment.

In using the TIM WOOD memory aid to analyze waste in Outage
Management projects, I hope I have increased your awareness of project waste
and some common sources of waste. With
this information, I hope you all will have smooth and efficient OMS
projects. If you have other suggestions
on where to find and prevent more waste in the project, I would love to hear
from you in the blog comments.